Effects of urban agglomeration and expansion on landscape connectivity in the river valley region, Qinghai-Tibet Plateau

Urbanization provides benefit to modern civilization, while it also creates a series of ecological issues at different scales. The study of landscape pattern and connectivity change caused by urban agglomeration is the hotspot of regional ecological security research. In this study, morphological spatial pattern analysis (MSPA) and Patch Importance Index (dPC) were used to evaluate landscape heterogeneity and landscape connectivity in the Huangshui River Valley, Qinghai-Tibet Plateau. Then the spatial relationship was revealed by bivariate spatial autocorrelation analysis and three-dimensional curved surface graph. The results showed that in the past 30 years, urbanization has increased more than 25%, with the decrease of farmland and the fluctuation of natural habitat. Heterogeneity and fragmentation were more obvious in the central region with great urban agglomeration. MSPA revealed significant spatial differences in the interaction between natural habitat and urbanization. The landscape connectivity of natural habitat in the central region was severely damaged by urban agglomeration and was spatially correlated with the landscape pattern index. Three-dimensional surface graph showed that the connectivity of farmland and natural habitat experienced fluctuation to decline trend with the expansion of construction land, which indicating a complex correlation and interaction between different land use types. In order to maintain the integrity of the ecosystem, it was necessary to take effective measures to improve the sustainability of cities and appropriately limit the expansion of urbanization. This study explored the landscape heterogeneity and connectivity from perspectives of the whole landscape, natural habitat, construction land, farmland and their correlation, which provided a theoretical basis for further optimization of urban coordinated ecological management.

Abstract licence: CC BY-NC

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.